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Recursive Learning of Feedforward and Compliance Compensation Parameters for Precision Motion Systems

Advanced Manufacturing

Summary

arXiv:2606.03533v1 Announce Type: new Abstract: To meet the stringent requirements of future motion systems exhibiting time-varying and/or position-dependent behavior, online data must be leveraged to improve control performance. This paper presents a recursive algorithm for simultaneous learning of feedforward and compliance compensation parameters. A multivariate regression formulation is proposed that jointly estimates friction, mass, jerk, and compliance compensation parameters while mitigating parameter coupling.

Why It Matters

This Advanced Manufacturing development raises the bar for precision and smart-factory capability in the region. For Asia, it is a signal worth tracking: it shapes who supplies, who scales, and who sets the standard over the next five years.

Key Facts

  • SectorAdvanced Manufacturing
  • Market
  • ImpactLow (42/100)
  • SignalResearch

Original Sources

arXiv Systems & Control ↗ https://arxiv.org/abs/2606.03533

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